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Telecom
Special Issues
Selected Papers from SEEDA-CECNSM 2021
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Selected Papers from SEEDA-CECNSM 2021

A special issue of Telecom (ISSN 2673-4001).

Deadline for manuscript submissions: closed (20 March 2022) | Viewed by 22390

Special Issue Editors

Prof. Dr. Markos G. Tsipouras

E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, University of Western Macedonia, GR50100 Kozani, Greece
Interests: biomedical signal processing; EEG signal processing; data mining; decision support and medical expert systems; data modelling; computational intelligence; image processing; biomedical engineering
Special Issues, Collections and Topics in MDPI journals
Dr. Alexandros Tzallas

E-Mail Website
Guest Editor
School of Applied Technology, Department of Computer Engineering, Technological Educational Institute of Epirus, Kostakioi, GR-47100 Arta, Greece
Interests: biomedical signal and image processing; EEG; wearable devices; computational intelligence; data modelling and decision support systems; biomedical engineering; medical physics
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Nikolaos Giannakeas

E-Mail Website
Guest Editor
School of Informatics and Telecommunications, Department of Informatics and Telecommunications, University of Ioannina, Kostakioi, GR-47100 Arta, Greece
Interests: biomedical image and signal processing; EEG signal processing; brain computer interface systems; wearable devices; bioinformatics; machine learning; biomedical engineering
Special Issues, Collections and Topics in MDPI journals
Dr. Katerina D. Tzimourta

E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, University of Western Macedonia, GR50100 Kozani, Greece
Interests: biomedical signal processing; EEG signal processing; brain–computer interface; machine learning; EEG wearable devices
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The 6th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM 2021) will take place in Preveza, Greece, from September 24 to 26, 2021. The SSEDA-CECNSM technical program includes all aspects of computer engineering from networks to design automation. This Special Issue aims at publishing extended versions of papers in the areas covered by the conference. Potential topics include (but are not limited to):

  • Computer networks and communications;
  • Social media and e-technologies;
  • Computer engineering;
  • Design automation

The extended accepted conference papers from SEEDA-CECNSM 2021 will be processed free of charge. 

Prof. Dr. Markos G. Tsipouras
Prof. Dr. Alexandros T. Tzallas
Prof. Dr. Nikolaos Giannakeas
Dr. Katerina D. Tzimourta
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Telecom is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • computer networks
  • security and privacy
  • social media and e-technologies
  • computer engineering
  • design automation

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

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Research

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21 pages, 2034 KiB  
Article
Stock Market Prediction Using Microblogging Sentiment Analysis and Machine Learning
by Paraskevas Koukaras, Christina Nousi and Christos Tjortjis
Telecom 2022, 3(2), 358-378; https://doi.org/10.3390/telecom3020019 - 27 May 2022
Cited by 36 | Viewed by 13043
Abstract
The use of Machine Learning (ML) and Sentiment Analysis (SA) on data from microblogging sites has become a popular method for stock market prediction. In this work, we developed a model for predicting stock movement utilizing SA on Twitter and StockTwits data. Stock [...] Read more.
The use of Machine Learning (ML) and Sentiment Analysis (SA) on data from microblogging sites has become a popular method for stock market prediction. In this work, we developed a model for predicting stock movement utilizing SA on Twitter and StockTwits data. Stock movement and sentiment data were used to evaluate this approach and validate it on Microsoft stock. We gathered tweets from Twitter and StockTwits, as well as financial data from Finance Yahoo. SA was applied to tweets, and seven ML classification models were implemented: K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Logistic Regression (LR), Naïve Bayes (NB), Decision Tree (DT), Random Forest (RF) and Multilayer Perceptron (MLP). The main novelty of this work is that it integrates multiple SA and ML methods, emphasizing the retrieval of extra features from social media (i.e., public sentiment), for improving stock prediction accuracy. The best results were obtained when tweets were analyzed using Valence Aware Dictionary and sEntiment Reasoner (VADER) and SVM. The top F-score was 76.3%, while the top Area Under Curve (AUC) value was 67%. Full article
(This article belongs to the Special Issue Selected Papers from SEEDA-CECNSM 2021)
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Review

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36 pages, 1763 KiB  
Review
LoRaWAN Communication Protocols: A Comprehensive Survey under an Energy Efficiency Perspective
by Konstantina Banti, Ioanna Karampelia, Thomas Dimakis, Alexandros-Apostolos A. Boulogeorgos, Thomas Kyriakidis and Malamati Louta
Telecom 2022, 3(2), 322-357; https://doi.org/10.3390/telecom3020018 - 25 May 2022
Cited by 16 | Viewed by 7982
Abstract
Long range wide area networks (LoRaWANs) have recently received intense scientific, research, and industrial interest. LoRaWANs play a pivotal role in Internet of Things (IoT) applications due to their capability to offer large coverage without sacrificing the energy efficiency and, thus the battery [...] Read more.
Long range wide area networks (LoRaWANs) have recently received intense scientific, research, and industrial interest. LoRaWANs play a pivotal role in Internet of Things (IoT) applications due to their capability to offer large coverage without sacrificing the energy efficiency and, thus the battery life, of end-devices. Most published contributions assume that LoRaWAN gateways (GWs) are plugged into the energy grid; thus, neglecting the network lifetime constraint due to power storage limitations. However, there are several verticals, including precision agriculture, forest protection, and others, in which it is difficult or even impossible to connect the GW to the power grid or to perform battery replacement at the end-devices. Consequently, maximizing the networks’ energy efficiency is expected to have a crucial impact on maximizing the network lifetime. Motivated by this, as well as the observation that the overall LoRaWAN network energy efficiency is significantly affected by the selected communication protocol, in this paper, we identify and discuss critical aspects and research challenges involved in the design of a LoRaWAN communication protocol, under an energy efficiency perspective. Building upon our findings, research directions towards a novel GreenLoRaWAN communication protocol are given, focusing on achieving energy efficiency, robustness, and scalability. Full article
(This article belongs to the Special Issue Selected Papers from SEEDA-CECNSM 2021)
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